The object of the present invention is a method of monitoring a rolling bearing of a machine, for example a textile machine, aimed at identifying a deviation of the bearing from a nominal performance in order to avoid the breakage thereof.
As is known, in order for a plant, for example a spinning line, to be economically remunerative, there is a need for it to work continuously, without interruptions due to sudden breakages of the machine components. Breakages of the components unfortunately are instead often unpredictable and the repairs required to restore machine operation often involve stopping the production for a more or less lengthy interval of time.
It is therefore very important to intervene in time on the machines in the plant, by executing scheduled interventions or interventions controlled by the monitoring system before the break occurs. Such a maintenance management approach is known with the expression “predictive maintenance”.
The monitoring system of physical quantities of machines of a spinning line set forth in International Application PCT/IB2015/053451 to the applicant, falls within such a background.
Typically, components having moving parts are involved in unexpected breakages due to fatigue and wear phenomena, conditions of use (for example, lack of adequate lubrication) or manufacturing defects of the component itself (for example, the presence of micro cracks or non-compliance of dimensional and geometrical tolerances).
The components most involved by unexpected breakages are the rolling bearings used for supporting in rotation the shafts of machines.
Today, monitoring systems of such bearings are known which by measuring amplitude, frequency or shape of the vibrating phenomena triggered by the bearings themselves, are capable of foreseeing the component breaking, often one or two hours before the breaking event occurs.
Due to the short notice, such systems unfortunately do not allow to schedule at best the stop of the machine and plant, and they force operators to perform sudden interventions.